Internal capital markets and return predictability in complex ownership firms

Singapore Management University SKBIPresented at American Finance Association Annual Meeting AFA 2019, January 4-6, Atlanta</p

Range Anxiety Among Battery Electric Vehicle Users: Both Distance and Waiting Time Matter

Range anxiety is a major concern of battery electric vehicles (BEVs) users or potential users. Previous work has explored the influential factors of distance-related range anxiety. However, time-related range anxiety has rarely been explored. The time cost when charging or waiting to charge the BEVs can negatively impact BEV users' experience. As a preliminary attempt, this survey study investigated time-related anxiety by observing BEV users' charging decisions in scenarios when both battery level and time cost are of concern. We collected and analyzed responses from 217 BEV users in mainland China. The results revealed that time-related anxiety exists and could affect users' charging decisions. Further, users' charging decisions can be a result of the trade-off between distance-related and time-related anxiety, and can be moderated by several external factors (e.g., regions and individual differences). The findings can support the optimization of charge station distribution and EV charge recommendation algorithms.Comment: Accepted by Human Factors and Ergonomics Society International Annual Meeting 202

An experimental investigation of supercritical CO2 accidental release from a pressurized pipeline

Experiments at laboratory scales have been conducted to investigate the behavior of the release of supercritical CO2 from pipelines including the rapid depressurization process and jet flow phenomena at different sizes of the leakage nozzle. The dry ice bank formed near the leakage nozzle is affected by the size of the leakage nozzle. The local Nusselt numbers at the leakage nozzle are calculated and the data indicate enhanced convective heat transfer for larger leakage holes. The mass outflow rates for different sizes of leakage holes are obtained and compared with two typical accidental gas release mathematical models. The results show that the “hole model” has a better prediction than the “modified model” for small leakage holes. The experiments provide fundamental data for the CO2 supercritical-gas multiphase flows in the leakage process, which can be used to guide the development of the leakage detection technology and risk assessment for the CO2 pipeline transportation

A modelling study of the multiphase leakage flow from pressurised CO2 pipeline

The accidental leakage is one of the main risks during the pipeline transportation of high pressure CO2. The decompression process of high pressure CO2 involves complex phase transition and large variations of the pressure and temperature fields. A mathematical method based on the homogeneous equilibrium mixture assumption is presented for simulating the leakage flow through a nozzle in a pressurised CO2 pipeline. The decompression process is represented by two sub-models: the flow in the pipe is represented by the blowdown model, while the leakage flow through the nozzle is calculated with the capillary tube assumption. In the simulation, two kinds of real gas equations of state were employed in this model instead of the ideal gas equation of state. Moreover, results of the flow through the nozzle and measurement data obtained from laboratory experiments of pressurised CO2 pipeline leakage were compared for the purpose of validation. The thermodynamic processes of the fluid both in the pipeline and the nozzle were described and analysed

Identifying the Riemann zeros by periodically driving a single qubit

The Riemann hypothesis, one of the most important open problems in pure mathematics, implies the most profound secret of prime numbers. One of the most interesting approaches to solve this hypothesis is to connect the problem with the spectrum of the physical Hamiltonian of a quantum system. However, none of the proposed quantum Hamiltonians have been experimentally feasible.Here, we report the first experiment to identify the first non-trivial zeros of the Riemann zeta function and the first two zeros of P\'olya's fake zeta function, using a novel Floquet method, through properly designed periodically driving functions. According to this method, the zeros of these functions are characterized by the occurrence of crossings of quasi-energies when the dynamics of the system are frozen. The experimentally obtained zeros are in excellent agreement with their exact values. Our study provides the first experimental realization of the Riemann zeros, which may provide new insights into this fundamental mathematical problem.Comment: 5 pages, 7 figure

The Effect of Nonlinear Charging Function and Line Change Constraints on Electric Bus Scheduling

The recharging plans are a key component of the electric bus schedule. Since the real-world charging function of electric vehicles follows a nonlinear relationship with the charging duration, it is challenging to accurately estimate the charging time. To provide a feasible bus schedule given the nonlinear charging function, this paper proposes a mixed integer programming model with a piecewise linear charging approximation and multi-depot and multi-vehicle type scheduling. The objective of the model is to minimise the total cost of the schedule, which includes the vehicle purchasing cost and operation cost. From a practical point of view, the number of line changes of each bus is also taken as one of the constraints in the optimisation. An improved heuristic algorithm is then proposed to find high-quality solutions of the problem with an efficient computation. Finally, a real-world dataset is used for the case study. The results of using different charging functions indicate a large deviation between the linear charging function and the piecewise linear approximation, which can effectively avoid the infeasible bus schedules. Moreover, the experiments show that the proposed line change constraints can be an effective control method for transit operators

CharacterChat: Learning towards Conversational AI with Personalized Social Support

In our modern, fast-paced, and interconnected world, the importance of mental well-being has grown into a matter of great urgency. However, traditional methods such as Emotional Support Conversations (ESC) face challenges in effectively addressing a diverse range of individual personalities. In response, we introduce the Social Support Conversation (S2Conv) framework. It comprises a series of support agents and the interpersonal matching mechanism, linking individuals with persona-compatible virtual supporters. Utilizing persona decomposition based on the MBTI (Myers-Briggs Type Indicator), we have created the MBTI-1024 Bank, a group that of virtual characters with distinct profiles. Through improved role-playing prompts with behavior preset and dynamic memory, we facilitate the development of the MBTI-S2Conv dataset, which contains conversations between the characters in the MBTI-1024 Bank. Building upon these foundations, we present CharacterChat, a comprehensive S2Conv system, which includes a conversational model driven by personas and memories, along with an interpersonal matching plugin model that dispatches the optimal supporters from the MBTI-1024 Bank for individuals with specific personas. Empirical results indicate the remarkable efficacy of CharacterChat in providing personalized social support and highlight the substantial advantages derived from interpersonal matching. The source code is available in \url{https://github.com/morecry/CharacterChat}.Comment: 10 pages, 6 figures, 5 table

Metabolic labelling of cholesteryl glucosides in Helicobacter pylori reveals how the uptake of human lipids enhances bacterial virulence.

Helicobacter pylori infects approximately half of the human population and is the main cause of various gastric diseases. This pathogen is auxotrophic for cholesterol, which it converts upon uptake to various cholesteryl α-glucoside derivatives, including cholesteryl 6'-acyl and 6'-phosphatidyl α-glucosides (CAGs and CPGs). Owing to a lack of sensitive analytical methods, it is not known if CAGs and CPGs play distinct physiological roles or how the acyl chain component affects function. Herein we established a metabolite-labelling method for characterising these derivatives qualitatively and quantitatively with a femtomolar detection limit. The development generated an MS/MS database of CGds, allowing for profiling of all the cholesterol-derived metabolites. The subsequent analysis led to the unprecedented information that these bacteria acquire phospholipids from the membrane of epithelial cells for CAG biosynthesis. The resulting increase in longer or/and unsaturated CAG acyl chains helps to promote lipid raft formation and thus delivery of the virulence factor CagA into the host cell, supporting the idea that the host/pathogen interplay enhances bacterial virulence. These findings demonstrate an important connection between the chain length of CAGs and the bacterial pathogenicity